Many digital image processing enhancements that improve the visual quality of a digital image, often an image of a scanned document, may rely on the accurate identification of different image regions within the digital image. Additionally, accurate detection of various regions in an image may be critical in many compression processes. Image characteristics may be used in the identification of image regions.
Scanned document images may contain a page background region of a dominant background color, for example the color of the paper stock on which the document was printed, and several local background regions, each with substantially-uniform color. Detecting and enhancing the colors of these regions may improve the appearance of the digital document image by reducing the amount of visible noise and color variation. For example, replacing the substantially-uniform color values of pixels in a background region with a single color value may improve visual quality. Such processing also may lead to significant gains in compression efficiency in document compression applications.
Background detection may become significantly more difficult as page complexity increases. A document may contain multiple regions that may be labeled as page background; for example, the scanner platen may be visible in a scanned document or the document may contain large local background areas. Color gradations, halftone backgrounds, large halftone and large continuous-tone areas with uniformly colored regions, and color text are some of the image components that may complicate detection of local background regions. Scanner artifacts and noise may make it difficult to accurately label all background pixels in a document image.